Show HN: The text disappears when you screenshot it

How the effect works (and implementation details)

• Text is visible only in motion: animated noise scrolls through text-shaped cutouts over static or differently-behaving background noise.
• Several comments note the claim “each frame is random noise” is not literally true in the demo: the pattern within letters visibly cycles / repeats, likely via a periodic function or buffer.
• Others point out it could be implemented with true per-frame random noise (like TV static) and still be readable as long as background is fixed.
• Alternative implementation ideas: shifting a noise buffer down each frame; re-randomizing letter pixels every frame; moving background vs. foreground in opposing directions.

Browser, zoom, and rendering quirks

• Multiple users report that zooming out (sometimes to ~25–65%) makes the text clearly readable and screenshots trivial.
• On some platforms (certain macOS/Chromium, Firefox/Android, Linux browsers with privacy / canvas protections), the animation fails or the background and text noise differ enough that text is visible even in static screenshots.
• Aliasing and luminance differences at certain zoom levels can unintentionally reveal the letters.

Ways to defeat “unscreenshottable” text

• Take two or more screenshots and:
  • XOR / difference / blend them in an editor (GIMP, Pixelmator, ImageMagick compare), or
  • Stack them with partial transparency, or
  • Blink between them in browser tabs (manual “blink comparator”).
• Record the screen instead of capturing a still; video preserves motion and reveals text.
• Use the URL query string which contains the text in plain form.
• Some users feed multiple frames to models or code interpreters to reconstruct the text.

Cameras, long exposure, and physical capture

• Long-exposure photography of the screen (e.g., 0.5s shutter) produces readable motion-blurred text on a noisy background.
• Even normal photos might be processable afterward to enhance the hidden text.

Applications, security, and ethics

• Suggested uses: “LLM-proof” or motion-based CAPTCHAs; friction against screenshot leaks; ID apps that hide sensitive fields from still captures; stylistic effect in games or technothrillers.
• Counterpoints: trivial to bypass with video, multiple screenshots, or AI; adds friction but not real security.
• Strong criticism for accessibility (low contrast, motion dependence, motion sickness, epilepsy triggers) and for making already-hostile CAPTCHAs worse.
• Some debate over user rights/ethics: attempts to block capture of on-screen content are seen by some as “annoying” or contrary to user ownership expectations.